code: def build_model(input_shape):
      """Build a logistic regression model with tf.keras."""
      model = keras.Sequential(
          [
              layers.Dense(
                  1,
                  use_bias=False,
                  activation="sigmoid",
                  input_shape=[input_shape],
              ),
          ]
      )
  
      model.compile(
          loss="binary_crossentropy",
          optimizer=tf.train.AdamOptimizer(),
          metrics=["accuracy"],
      )
  
      return model
  
file_path: tf-encrypted/examples/application/house-credit-default/main.py
imports: import argparse
  import os
  import time
  import tensorflow
  import tf2onnx
  from tensorflow import keras
  from tensorflow.keras import layers
  from tensorflow.python import errors_impl
  from utils import data_prep
  from utils import read_one_row
label_desc: Use image node_id 3 for calling a global function with example usage: build_model(input_shape) and returns: model